code: def _input_layer_specs(self):
      return {
          "img": tf.TensorSpec(
              [
                  None,
                  self._params.line_height,
                  self._params.input_channels,
              ],
              dtype=tf.uint8,
          ),
          "img_len": tf.TensorSpec([1], dtype=tf.int32),
      }
  
imports: import logging
  import os
  from typing import Type, Optional
  import tensorflow
  from tfaip.data.data import DataBase
  from tfaip.data.databaseparams import DataPipelineParams
  from tfaip.data.pipeline.datapipeline import DataPipeline
  from tfaip.data.pipeline.definitions import PipelineMode, INPUT_PROCESSOR
  from tfaip.data.pipeline.processor.params import SequentialProcessorPipelineParams
  from calamari_ocr.ocr.augmentation.dataaugmentationparams import DataAugmentationAmount
  from calamari_ocr.ocr.dataset.datareader.base import CalamariDataGeneratorParams
  from calamari_ocr.ocr.dataset.datareader.file import FileDataParams
  from calamari_ocr.ocr.dataset.imageprocessors.augmentation import AugmentationProcessorParams
  from calamari_ocr.ocr.dataset.imageprocessors.default_image_processors import default_image_processors
  from calamari_ocr.ocr.dataset.imageprocessors.preparesample import PrepareSampleProcessorParams
  from calamari_ocr.ocr.dataset.params import DataParams
  from calamari_ocr.ocr.dataset.pipeline import CalamariPipeline
  from calamari_ocr.ocr.dataset.postprocessors.ctcdecoder import CTCDecoderProcessorParams
  from calamari_ocr.ocr.dataset.postprocessors.reshape import ReshapeOutputsProcessorParams
  from calamari_ocr.ocr.dataset.textprocessors.default_text_processor import default_text_pre_processors
  from calamari_ocr.utils.image import ImageLoaderParams
label_desc: Use image node_id 3 for calling the Data obj's underlying member method code with example usage: obj._input_layer_specs() and returns: dict